Vignettes for PI Charter
Mike Verhoeven
2024-10-18
#To-do: 1. Snowcover effects on clp abund for all lakes where the DB has multiple CLP projects - non-local winter data -
- Compare my results to old ones! Lake past, neighbors, watershed, state?
Prep WS
#load libraries
library(data.table)
library(tidyr)
library(stringr)
library(ggplot2)
library(plotly)##
## Attaching package: 'plotly'## The following object is masked from 'package:ggplot2':
##
## last_plot## The following object is masked from 'package:stats':
##
## filter## The following object is masked from 'package:graphics':
##
## layout#import Data
surveys <- fread("scripts&data/data/input/lake_year_data.csv")
rawdata <- fread("scripts&data/data/input/PCRIsurveysPICharter2srt_sheet1rawdata.csv")#data explore
#see if we can re-generate ray's calc'd CLP values
head(rawdata)## V1 SUBMITTER_NAME SUBMITTER_EMAIL DOW SURVEY_START RAKE_MAX
## <int> <char> <char> <int> <char> <char>
## 1: 34744 DNR Fisheries <NA> 1000100 6/25/2008 Unknown
## 2: 34745 DNR Fisheries <NA> 1000100 6/25/2008 Unknown
## 3: 34746 DNR Fisheries <NA> 1000100 6/25/2008 Unknown
## 4: 34747 DNR Fisheries <NA> 1000100 6/25/2008 Unknown
## 5: 34748 DNR Fisheries <NA> 1000100 6/25/2008 Unknown
## 6: 34749 DNR Fisheries <NA> 1000100 6/25/2008 Unknown
## SUBMIT_TIME SURVEYORS sta_nbr latitude longitude
## <char> <char> <char> <num> <num>
## 1: <NA> Unnamed hardworking surveyor(s) 18520 46.17630 -93.09180
## 2: <NA> Unnamed hardworking surveyor(s) 18521 46.17681 -93.08801
## 3: <NA> Unnamed hardworking surveyor(s) 18522 46.18594 -93.07455
## 4: <NA> Unnamed hardworking surveyor(s) 18523 46.18594 -93.07371
## 5: <NA> Unnamed hardworking surveyor(s) 18524 46.18594 -93.07287
## 6: <NA> Unnamed hardworking surveyor(s) 18525 46.18594 -93.07202
## depth_ft substrate whole_rake_density myriophyllum_spicatum
## <char> <char> <int> <char>
## 1: 2.3 <NA> NA 0
## 2: 4.8 <NA> NA 0
## 3: 6.3 <NA> NA 0
## 4: 7.5 <NA> NA 0
## 5: 3.1 <NA> NA 0
## 6: 1 <NA> NA 0
## potamogeton_crispus ceratophyllum_demersum chara_sp elodea_canadensis
## <char> <char> <char> <char>
## 1: 0 0 0 0
## 2: 0 0 0 1
## 3: 0 1 0 0
## 4: 0 0 0 0
## 5: 1 1 0 0
## 6: 0 0 0 0
## lemna_minor lemna_trisulca nitella_sp nymphaea_odorata phalaris_arundinacea
## <char> <char> <int> <char> <char>
## 1: 0 1 0 0 0
## 2: 0 1 0 0 0
## 3: 0 0 0 0 0
## 4: 0 0 0 0 0
## 5: 0 1 0 0 0
## 6: 0 0 0 0 0
## potamogeton_amplifolius potamogeton_foliosus potamogeton_pusillus
## <char> <char> <char>
## 1: 0 0 0
## 2: 0 0 0
## 3: 0 0 0
## 4: 0 0 0
## 5: 1 0 0
## 6: 0 0 0
## potamogeton_robbinsii potamogeton_zosteriformis ranunculus_aquatilis
## <char> <char> <char>
## 1: 0 1 0
## 2: 0 0 0
## 3: 0 0 0
## 4: 0 0 0
## 5: 0 0 0
## 6: 0 0 0
## spirodela_polyrrhiza typha_angustifolia vallisneria_americana
## <char> <char> <char>
## 1: 1 0 0
## 2: 0 0 0
## 3: 0 0 0
## 4: 0 0 0
## 5: 0 0 0
## 6: 0 0 0
## wolffia_columbiana aquatic_moss heteranthera_dubia najas_guadalupensis
## <int> <char> <char> <char>
## 1: 0 <NA> 0 0
## 2: 0 <NA> 0 0
## 3: 0 <NA> 0 0
## 4: 0 <NA> 0 0
## 5: 0 <NA> 0 0
## 6: 0 <NA> 0 0
## phragmites_australis potamogeton_friesii potamogeton_gramineus
## <char> <char> <int>
## 1: 0 0 0
## 2: 0 0 0
## 3: 0 0 0
## 4: 0 0 0
## 5: 0 0 0
## 6: 0 0 0
## potamogeton_illinoensis potamogeton_natans schoenoplectus_acutus
## <char> <char> <char>
## 1: 0 0 1
## 2: 0 0 0
## 3: 0 0 0
## 4: 0 0 0
## 5: 0 0 0
## 6: 0 0 0
## stuckenia_pectinata lythrum_salicaria brasenia_schreberi
## <char> <char> <char>
## 1: 0 0 0
## 2: 0 0 0
## 3: 0 0 0
## 4: 0 0 0
## 5: 0 0 0
## 6: 0 0 0
## eleocharis_acicularis eleocharis_erythropoda najas_flexilis
## <char> <char> <char>
## 1: 0 0 0
## 2: 0 0 0
## 3: 0 0 0
## 4: 0 0 0
## 5: 0 0 0
## 6: 0 0 0
## potamogeton_nodosus potamogeton_praelongus sagittaria_rigida
## <char> <char> <char>
## 1: 0 0 0
## 2: 0 0 0
## 3: 0 0 0
## 4: 0 0 0
## 5: 0 0 0
## 6: 0 0 0
## schoenoplectus_tabernaemontani lychnothamnus_barbatus
## <char> <char>
## 1: 1 0
## 2: 0 0
## 3: 0 0
## 4: 0 0
## 5: 0 0
## 6: 0 0
## calamagrostis_canadensis utricularia_vulgaris zannichellia_palustris
## <char> <char> <char>
## 1: 0 0 0
## 2: 0 0 0
## 3: 0 0 0
## 4: 0 0 0
## 5: 0 0 0
## 6: 0 0 0
## alisma_triviale bolboschoenus_fluviatilis myriophyllum_sibiricum
## <char> <char> <char>
## 1: 0 0 0
## 2: 0 0 0
## 3: 0 0 0
## 4: 0 0 0
## 5: 0 0 0
## 6: 0 0 0
## sagittaria_latifolia sagittaria_montevidensis sparganium_eurycarpum
## <char> <char> <char>
## 1: 0 <NA> 0
## 2: 0 <NA> 0
## 3: 0 <NA> 0
## 4: 0 <NA> 0
## 5: 0 <NA> 0
## 6: 0 <NA> 0
## leersia_oryzoides iris_pseudacorus iris_virginica ceratophyllum_echinatum
## <char> <char> <char> <char>
## 1: 0 <NA> 0 0
## 2: 0 <NA> 0 0
## 3: 0 <NA> 0 0
## 4: 0 <NA> 0 0
## 5: 0 <NA> 0 0
## 6: 0 <NA> 0 0
## riccia_fluitans potamogeton_richardsonii nuphar_variegata
## <char> <char> <char>
## 1: 0 0 0
## 2: 0 0 0
## 3: 0 0 0
## 4: 0 0 0
## 5: 0 0 1
## 6: 0 1 1
## myriophyllum_spicatum_x_sibiricum sagittaria_cristata najas_minor
## <char> <char> <char>
## 1: <NA> 0 0
## 2: <NA> 0 0
## 3: <NA> 0 0
## 4: <NA> 0 0
## 5: <NA> 0 0
## 6: <NA> 0 0
## carex_comosa typha_x_glauca carex_pellita carex_scoparia sagittaria_sp
## <char> <char> <int> <int> <char>
## 1: 0 0 0 0 0
## 2: 0 0 0 0 0
## 3: 0 0 0 0 0
## 4: 0 0 0 0 0
## 5: 0 0 0 0 0
## 6: 0 0 0 0 0
## sparganium_sp iris_sp sta_nbr.1 stuckenia_filiformis sta_nbr.2 scirpus_sp
## <int> <int> <char> <int> <lgcl> <char>
## 1: 0 0 <NA> 0 NA 0
## 2: 0 0 <NA> 0 NA 0
## 3: 0 0 <NA> 0 NA 0
## 4: 0 0 <NA> 0 NA 0
## 5: 0 0 <NA> 0 NA 0
## 6: 0 0 <NA> 0 NA 0
## utricularia_minor riccia_sp wolffia_sp nitella_furcata juncus_pelocarpus
## <char> <int> <char> <lgcl> <int>
## 1: 0 0 0 NA 0
## 2: 0 0 0 NA 0
## 3: 0 0 0 NA 0
## 4: 0 0 0 NA 0
## 5: 0 0 0 NA 0
## 6: 0 0 0 NA 0
## nelumbo_lutea isoetes_echinospora sagittaria_graminea cyperus_sp
## <char> <int> <int> <lgcl>
## 1: 0 0 0 NA
## 2: 0 0 0 NA
## 3: 0 0 0 NA
## 4: 0 0 0 NA
## 5: 0 0 0 NA
## 6: 0 0 0 NA
## hydrocotyle_ranunculoides bidens_beckii nitella_tenuissima nitella_flexilis
## <int> <int> <lgcl> <lgcl>
## 1: NA 0 NA NA
## 2: NA 0 NA NA
## 3: NA 0 NA NA
## 4: NA 0 NA NA
## 5: NA 0 NA NA
## 6: NA 0 NA NA
## typha_sp drepanocladus_sp najas_sp utricularia_sp utricularia_sp.1
## <char> <int> <int> <int> <lgcl>
## 1: 0 0 0 0 NA
## 2: 0 0 0 0 NA
## 3: 0 0 0 0 NA
## 4: 0 0 0 0 NA
## 5: 0 0 0 0 NA
## 6: 0 0 0 0 NA
## ranunculus_sp chara_sp.1 elodea_sp hippuris_vulgaris caltha_palustris
## <int> <lgcl> <int> <int> <int>
## 1: 0 NA 0 0 0
## 2: 0 NA 0 0 0
## 3: 0 NA 0 0 0
## 4: 0 NA 0 0 0
## 5: 0 NA 0 0 0
## 6: 0 NA 0 0 0
## potamogeton_strictifolius no_veg_found elodea_nuttallii lemna_sp
## <int> <char> <int> <num>
## 1: 0 <NA> 0 0
## 2: 0 <NA> 0 0
## 3: 0 <NA> 0 0
## 4: 0 <NA> 0 0
## 5: 0 <NA> 0 0
## 6: 0 <NA> 0 0
## ludwigia_palustris myriophyllum_verticillatum najas_marina
## <int> <char> <int>
## 1: NA 0 0
## 2: NA 0 0
## 3: NA 0 0
## 4: NA 0 0
## 5: NA 0 0
## 6: NA 0 0
## persicaria_amphibia stuckenia_vaginata solanum_dulcamara
## <char> <int> <lgcl>
## 1: 0 0 NA
## 2: 0 0 NA
## 3: 0 0 NA
## 4: 0 0 NA
## 5: 0 0 NA
## 6: 0 0 NA
## schoenoplectus_pungens lake_name plant_height surface_growth
## <int> <char> <num> <num>
## 1: 0 pine NA NA
## 2: 0 pine NA NA
## 3: 0 pine NA NA
## 4: 0 pine NA NA
## 5: 0 pine NA NA
## 6: 0 pine NA NA
## equisetum_fluviatile fontinalis_antipyretica lemna_turionifera x y
## <char> <int> <int> <num> <num>
## 1: 0 0 0 NA NA
## 2: 0 0 0 NA NA
## 3: 0 0 0 NA NA
## 4: 0 0 0 NA NA
## 5: 0 0 0 NA NA
## 6: 0 0 0 NA NA
## utricularia_gibba nostoc_sp bidens_cernua phragmites_australis_americanus
## <int> <lgcl> <lgcl> <lgcl>
## 1: 0 NA NA NA
## 2: 0 NA NA NA
## 3: 0 NA NA NA
## 4: 0 NA NA NA
## 5: 0 NA NA NA
## 6: 0 NA NA NA
## potamogeton_sp potamogeton_obtusifolius typha_latifolia lemna_gibba
## <int> <int> <int> <lgcl>
## 1: 0 0 0 NA
## 2: 0 0 0 NA
## 3: 0 0 0 NA
## 4: 0 0 0 NA
## 5: 0 0 0 NA
## 6: 0 0 0 NA
## potamogeton_alpinus dulichium_arundinaceum phragmites_australis_australis
## <int> <int> <lgcl>
## 1: 0 0 NA
## 2: 0 0 NA
## 3: 0 0 NA
## 4: 0 0 NA
## 5: 0 0 NA
## 6: 0 0 NA
## acorus_americanus sparganium_emersum zizania_palustris nitellopsis_obtusa
## <int> <int> <char> <int>
## 1: 0 0 0 0
## 2: 0 0 0 0
## 3: 0 0 0 0
## 4: 0 0 0 0
## 5: 0 0 0 0
## 6: 0 0 0 0
## ranunculus_flabellaris phragmites_sp zizania_sp chara_contraria
## <int> <lgcl> <int> <lgcl>
## 1: 0 NA 0 NA
## 2: 0 NA 0 NA
## 3: 0 NA 0 NA
## 4: 0 NA 0 NA
## 5: 0 NA 0 NA
## 6: 0 NA 0 NA
## chara_braunii schoenoplectus_heterochaetus sagittaria_cuneata
## <lgcl> <lgcl> <int>
## 1: NA NA 0
## 2: NA NA 0
## 3: NA NA 0
## 4: NA NA 0
## 5: NA NA 0
## 6: NA NA 0
## ranunculus_flammula pontederia_cordata nitella_macounii isoetes_lacustris
## <int> <int> <lgcl> <lgcl>
## 1: 0 0 NA NA
## 2: 0 0 NA NA
## 3: 0 0 NA NA
## 4: 0 0 NA NA
## 5: 0 0 NA NA
## 6: 0 0 NA NA
## lobelia_dortmanna myriophyllum_tenellum iris_versicolor carex_stricta
## <int> <int> <int> <char>
## 1: 0 0 0 <NA>
## 2: 0 0 0 <NA>
## 3: 0 0 0 <NA>
## 4: 0 0 0 <NA>
## 5: 0 0 0 <NA>
## 6: 0 0 0 <NA>
## veronica_catenata eleocharis_palustris nymphaea_odorata.1 nuphar_advena
## <char> <int> <int> <int>
## 1: <NA> 0 0 0
## 2: <NA> 0 0 0
## 3: <NA> 0 0 0
## 4: <NA> 0 0 0
## 5: <NA> 0 0 0
## 6: <NA> 0 0 0
## utm_crs heteranthera_dubia.1 plant_height_m carex_sp utricularia_geminiscapa
## <int> <lgcl> <lgcl> <int> <int>
## 1: NA NA NA 0 0
## 2: NA NA NA 0 0
## 3: NA NA NA 0 0
## 4: NA NA NA 0 0
## 5: NA NA NA 0 0
## 6: NA NA NA 0 0
## carex_lacustris najas_sp.1 unk_sp typha_latifolia.1 impatiens_sp
## <int> <lgcl> <int> <lgcl> <int>
## 1: 0 NA NA NA 0
## 2: 0 NA NA NA 0
## 3: 0 NA NA NA 0
## 4: 0 NA NA NA 0
## 5: 0 NA NA NA 0
## 6: 0 NA NA NA 0
## rumex_britannica thelypteris_palustris characeae potamogeton_perfoliatus
## <int> <lgcl> <int> <lgcl>
## 1: 0 NA NA NA
## 2: 0 NA NA NA
## 3: 0 NA NA NA
## 4: 0 NA NA NA
## 5: 0 NA NA NA
## 6: 0 NA NA NA
## potamogeton_epihydrus schoenoplectus_sp not_sampled utricularia_intermedia
## <int> <int> <lgcl> <int>
## 1: 0 0 NA 0
## 2: 0 0 NA 0
## 3: 0 0 NA 0
## 4: 0 0 NA 0
## 5: 0 0 NA 0
## 6: 0 0 NA 0
## survey_notes algae algae.1 nuphar_sp nymphaea_sp equisetum_sp
## <char> <char> <int> <char> <char> <int>
## 1: <NA> <NA> NA 1 1 1
## 2: <NA> <NA> NA 0 0 0
## 3: <NA> <NA> NA 0 0 0
## 4: <NA> <NA> NA 0 0 0
## 5: <NA> <NA> NA 0 0 0
## 6: <NA> <NA> NA 0 0 0
## freshwater_sponge myriophyllum_sp potamogeton_spirillus sparganium_fluctuans
## <lgcl> <int> <int> <int>
## 1: NA 0 0 0
## 2: NA 0 0 0
## 3: NA 0 0 0
## 4: NA 0 0 0
## 5: NA 0 0 0
## 6: NA 0 0 0
## subbasin multipartsurvey acorus_sp alisma_sp alnus_sp andromeda_polifolia
## <char> <num> <int> <int> <int> <int>
## 1: NA 0 0 0 0
## 2: NA 0 0 0 0
## 3: NA 0 0 0 0
## 4: NA 0 0 0 0
## 5: NA 0 0 0 0
## 6: NA 0 0 0 0
## asclepias_incarnata asteraceae_taxa azolla_microphylla betula_pumila
## <int> <int> <int> <int>
## 1: 0 0 0 0
## 2: 0 0 0 0
## 3: 0 0 0 0
## 4: 0 0 0 0
## 5: 0 0 0 0
## 6: 0 0 0 0
## bidens_sp bolboschoenus_maritimus boltonia_asteroides butomus_umbellatus
## <int> <int> <int> <int>
## 1: 0 NA 0 0
## 2: 0 NA 0 0
## 3: 0 NA 0 0
## 4: 0 NA 0 0
## 5: 0 NA 0 0
## 6: 0 NA 0 0
## calla_palustris callitriche_sp carex_aquatilis ceratophyllum_sp
## <int> <int> <int> <int>
## 1: 0 0 0 0
## 2: 0 0 0 0
## 3: 0 0 0 0
## 4: 0 0 0 0
## 5: 0 0 0 0
## 6: 0 0 0 0
## chamaedaphne_calyculata chara_canescens chara_globularis characeae_taxa
## <int> <int> <int> <int>
## 1: 0 0 0 0
## 2: 0 0 0 0
## 3: 0 0 0 0
## 4: 0 0 0 0
## 5: 0 0 0 0
## 6: 0 0 0 0
## cicuta_sp cicuta_maculata cyperaceae_taxa drepanocladus_aduncus elatine_sp
## <int> <int> <int> <int> <int>
## 1: 0 0 0 0 0
## 2: 0 0 0 0 0
## 3: 0 0 0 0 0
## 4: 0 0 0 0 0
## 5: 0 0 0 0 0
## 6: 0 0 0 0 0
## elatine_minima eleocharis_sp eleocharis_robbinsii eragrostis_sp
## <int> <int> <int> <int>
## 1: 0 0 0 0
## 2: 0 0 0 0
## 3: 0 0 0 0
## 4: 0 0 0 0
## 5: 0 0 0 0
## 6: 0 0 0 0
## eriocaulon_aquaticum eutrochium_dubium eutrochium_maculatum
## <int> <int> <int>
## 1: 0 0 0
## 2: 0 0 0
## 3: 0 0 0
## 4: 0 0 0
## 5: 0 0 0
## 6: 0 0 0
## eupatorium_perfoliatum eutrochium_sp fontinalis_sullivantii
## <int> <int> <int>
## 1: 0 0 0
## 2: 0 0 0
## 3: 0 0 0
## 4: 0 0 0
## 5: 0 0 0
## 6: 0 0 0
## glyceria_borealis hypericum_sp hypericum_ellipticum impatiens_capensis
## <int> <int> <int> <int>
## 1: 0 0 0 0
## 2: 0 0 0 0
## 3: 0 0 0 0
## 4: 0 0 0 0
## 5: 0 0 0 0
## 6: 0 0 0 0
## isoetes_sp juncus_sp juncus_arcticus juncus_canadensis juncus_effusus
## <int> <int> <int> <int> <int>
## 1: 0 0 0 0 0
## 2: 0 0 0 0 0
## 3: 0 0 0 0 0
## 4: 0 0 0 0 0
## 5: 0 0 0 0 0
## 6: 0 0 0 0 0
## lamiaceae_taxa rhododendron_groenlandicum littorella_uniflora
## <int> <int> <int>
## 1: 0 0 0
## 2: 0 0 0
## 3: 0 0 0
## 4: 0 0 0
## 5: 0 0 0
## 6: 0 0 0
## lycopus_americanus lysimachia_sp lysimachia_terrestris menyanthes_trifoliata
## <int> <int> <int> <int>
## 1: 0 0 0 0
## 2: 0 0 0 0
## 3: 0 0 0 0
## 4: 0 0 0 0
## 5: 0 0 0 0
## 6: 0 0 0 0
## myrica_gale myriophyllum_alterniflorum myriophyllum_farwellii
## <int> <int> <int>
## 1: 0 0 0
## 2: 0 0 0
## 3: 0 0 0
## 4: 0 0 0
## 5: 0 0 0
## 6: 0 0 0
## najas_gracillima nasturtium_officinale nitellopsis_sp nuphar_microphylla
## <int> <int> <int> <int>
## 1: 0 0 NA 0
## 2: 0 0 NA 0
## 3: 0 0 NA 0
## 4: 0 0 NA 0
## 5: 0 0 NA 0
## 6: 0 0 NA 0
## nymphaea_leibergii nymphaeaceae_taxa persicaria_sp persicaria_lapathifolia
## <int> <int> <int> <int>
## 1: 0 0 0 0
## 2: 0 0 0 0
## 3: 0 0 0 0
## 4: 0 0 0 0
## 5: 0 0 0 0
## 6: 0 0 0 0
## poaceae_taxa potamogeton_bicupulatus potamogeton_diversifolius
## <int> <int> <int>
## 1: 0 0 0
## 2: 0 0 0
## 3: 0 0 0
## 4: 0 0 0
## 5: 0 0 0
## 6: 0 0 0
## potamogeton_hillii potamogeton_vaseyi ricciocarpos_natans ruppia_cirrhosa
## <int> <int> <int> <int>
## 1: 0 0 0 0
## 2: 0 0 0 0
## 3: 0 0 0 0
## 4: 0 0 0 0
## 5: 0 0 0 0
## 6: 0 0 0 0
## salix_sp schoenoplectus_subterminalis schoenoplectus_x_oblongus
## <int> <int> <int>
## 1: 0 0 0
## 2: 0 0 0
## 3: 0 0 0
## 4: 0 0 0
## 5: 0 0 0
## 6: 0 0 0
## scirpus_atrovirens scirpus_cyperinus scolochloa_festucacea
## <int> <int> <int>
## 1: 0 0 0
## 2: 0 0 0
## 3: 0 0 0
## 4: 0 0 0
## 5: 0 0 0
## 6: 0 0 0
## scorpidium_scorpioides scutellaria_sp scutellaria_lateriflora sium_suave
## <int> <int> <int> <int>
## 1: 0 0 NA 0
## 2: 0 0 NA 0
## 3: 0 0 NA 0
## 4: 0 0 NA 0
## 5: 0 0 NA 0
## 6: 0 0 NA 0
## solidago_sp sparganium_americanum sparganium_angustifolium sparganium_natans
## <int> <int> <int> <int>
## 1: 0 0 0 0
## 2: 0 0 0 0
## 3: 0 0 0 0
## 4: 0 0 0 0
## 5: 0 0 0 0
## 6: 0 0 0 0
## sphagnum_sp sphagnum_magellanicum stuckenia_sp tolypella_intricata
## <int> <int> <int> <int>
## 1: 0 0 0 0
## 2: 0 0 0 0
## 3: 0 0 0 0
## 4: 0 0 0 0
## 5: 0 0 0 0
## 6: 0 0 0 0
## triadenum_fraseri utricularia_purpurea verbena_sp veronica_americana
## <int> <int> <int> <int>
## 1: 0 0 0 NA
## 2: 0 0 0 NA
## 3: 0 0 0 NA
## 4: 0 0 0 NA
## 5: 0 0 0 NA
## 6: 0 0 0 NA
## wolffia_borealis heteranthera_sp ranunculus_sceleratus guid
## <int> <int> <lgcl> <lgcl>
## 1: 0 0 NA NA
## 2: 0 0 NA NA
## 3: 0 0 NA NA
## 4: 0 0 NA NA
## 5: 0 0 NA NA
## 6: 0 0 NA NA
## decodon_verticillatus spirogyra_sp lemnaceae_taxa elodea_sp.1
## <lgcl> <int> <lgcl> <lgcl>
## 1: NA NA NA NA
## 2: NA NA NA NA
## 3: NA NA NA NA
## 4: NA NA NA NA
## 5: NA NA NA NA
## 6: NA NA NA NA
## comarum_palustre scirpus_sp.1 lysimachia_sp.1 typha_sp.1
## <int> <lgcl> <lgcl> <lgcl>
## 1: 0 NA NA NA
## 2: 0 NA NA NA
## 3: 0 NA NA NA
## 4: 0 NA NA NA
## 5: 0 NA NA NA
## 6: 0 NA NA NA
## potamogeton_obtusifolius.1 glyceria_canadensis utricularia_intermedia.1
## <lgcl> <lgcl> <lgcl>
## 1: NA NA NA
## 2: NA NA NA
## 3: NA NA NA
## 4: NA NA NA
## 5: NA NA NA
## 6: NA NA NA
## myriophyllum_sp.1 percent_biovolume plant_height.1 spirodela_sp
## <lgcl> <num> <num> <int>
## 1: NA NA NA NA
## 2: NA NA NA NA
## 3: NA NA NA NA
## 4: NA NA NA NA
## 5: NA NA NA NA
## 6: NA NA NA NA
## vallisneria_sp fontinalis_sp unk_sp.1 nitella_sp.1 cyanobacteria
## <int> <lgcl> <int> <int> <int>
## 1: NA NA NA NA NA
## 2: NA NA NA NA NA
## 3: NA NA NA NA NA
## 4: NA NA NA NA NA
## 5: NA NA NA NA NA
## 6: NA NA NA NA NA
## nitella_mucronata andromeda_polifolia.1 eleocharis_palustris.1
## <lgcl> <lgcl> <int>
## 1: NA NA NA
## 2: NA NA NA
## 3: NA NA NA
## 4: NA NA NA
## 5: NA NA NA
## 6: NA NA NA
## myriophyllum_sibiricum.1 persicaria_amphibia.1 potamogeton_sp.1
## <int> <int> <int>
## 1: NA NA 0
## 2: NA NA 0
## 3: NA NA 0
## 4: NA NA 0
## 5: NA NA 0
## 6: NA NA 0
## ranunculus_aquatilis.1 schoenoplectus_sp.1 schoenoplectus_tabernaemontani.1
## <int> <int> <int>
## 1: NA NA 0
## 2: NA NA NA
## 3: NA NA NA
## 4: NA NA NA
## 5: NA NA NA
## 6: NA NA NA
## sparganium_sp.1 sparganium_sp.2 utricularia_vulgaris.1
## <int> <int> <int>
## 1: 0 NA NA
## 2: 0 NA NA
## 3: 0 NA NA
## 4: 0 NA NA
## 5: 0 NA NA
## 6: 0 NA NA
## spirodela_polyrrhiza.1
## <int>
## 1: NA
## 2: NA
## 3: NA
## 4: NA
## 5: NA
## 6: NA rawdata[ , .N , .(SURVEY_START, DOW) ]## SURVEY_START DOW N
## <char> <int> <int>
## 1: 6/25/2008 1000100 85
## 2: 6/18/2012 1010400 34
## 3: 6/8/2011 1010500 80
## 4: 5/24/2010 1014200 216
## 5: 6/21/2012 1014900 43
## ---
## 956: 6/20/2005 86023400 181
## 957: 6/25/2017 86025200 836
## 958: 6/27/2013 86025500 39
## 959: 4/22/2017 86026400 158
## 960: 6/20/2007 86047000 33 names(rawdata)[str_detect(names(rawdata), "pota")]## [1] "potamogeton_crispus" "potamogeton_amplifolius"
## [3] "potamogeton_foliosus" "potamogeton_pusillus"
## [5] "potamogeton_robbinsii" "potamogeton_zosteriformis"
## [7] "potamogeton_friesii" "potamogeton_gramineus"
## [9] "potamogeton_illinoensis" "potamogeton_natans"
## [11] "potamogeton_nodosus" "potamogeton_praelongus"
## [13] "potamogeton_richardsonii" "potamogeton_strictifolius"
## [15] "potamogeton_sp" "potamogeton_obtusifolius"
## [17] "potamogeton_alpinus" "potamogeton_perfoliatus"
## [19] "potamogeton_epihydrus" "potamogeton_spirillus"
## [21] "potamogeton_bicupulatus" "potamogeton_diversifolius"
## [23] "potamogeton_hillii" "potamogeton_vaseyi"
## [25] "potamogeton_obtusifolius.1" "potamogeton_sp.1"#alltime max vet depth
a <- rawdata[ , .("survey_ident"= .GRP, "totnsamp" = .N, "clpN" = sum(potamogeton_crispus >= 1, na.rm = T), "lat_median" = median(latitude, na.rm = T), "lon_median" = median(longitude, na.rm = T)) , , .(SURVEY_START, DOW) ][ , clpfoc := clpN/totnsamp ,]
#get snow data https://www.wrcc.dri.edu/cgi-bin/cliMAIN.pl?mn5435
snow <- fread("scripts&data/data/input/MSP_snowfall_alltime.csv")
snow## Winter_end_year JUL AUG SEP OCT NOV DEC JAN FEB MAR APR
## <int> <int> <int> <num> <num> <num> <num> <num> <num> <num> <num>
## 1: 1939 0 0 0.0 1.9 0.5 9.1 7.4 11.0 6.0 3.9
## 2: 1940 0 0 0.0 0.6 0.0 4.8 5.0 9.1 25.6 0.0
## 3: 1941 0 0 0.0 0.0 26.3 10.6 3.3 5.5 6.8 0.0
## 4: 1942 0 0 0.0 0.0 3.8 8.6 1.7 5.2 4.6 0.0
## 5: 1943 0 0 1.7 0.3 0.9 7.0 10.1 4.6 9.8 0.0
## 6: 1944 0 0 0.0 0.0 10.3 0.0 1.0 4.2 11.1 0.3
## 7: 1945 0 0 0.0 0.0 2.5 1.1 8.2 15.4 0.7 6.0
## 8: 1946 0 0 0.0 0.0 4.5 14.6 4.3 11.9 1.5 0.1
## 9: 1947 0 0 0.0 0.0 4.1 5.9 7.6 1.9 3.3 2.0
## 10: 1948 0 0 0.0 0.0 21.8 6.7 3.5 11.6 5.2 0.3
## 11: 1949 0 0 0.0 0.0 2.5 2.3 12.5 3.4 8.3 9.3
## 12: 1950 0 0 0.0 0.0 2.7 6.5 17.0 7.9 11.1 6.4
## 13: 1951 0 0 0.0 0.0 5.6 25.0 7.1 8.6 40.0 2.6
## 14: 1952 0 0 0.0 0.8 10.8 16.5 9.9 15.0 25.4 0.6
## 15: 1953 0 0 0.0 0.0 10.1 6.0 6.0 13.4 6.7 0.7
## 16: 1954 0 0 0.0 0.0 1.9 5.9 3.6 1.0 10.7 0.2
## 17: 1955 0 0 0.0 0.4 6.4 4.0 7.8 11.0 4.3 0.0
## 18: 1956 0 0 0.0 2.5 6.0 14.6 4.6 2.4 14.0 1.1
## 19: 1957 0 0 0.0 0.0 6.8 2.1 4.9 8.7 7.0 9.6
## 20: 1958 0 0 0.0 0.0 10.3 2.2 2.4 1.2 3.5 1.6
## 21: 1959 0 0 0.0 0.0 3.3 2.4 1.4 6.3 5.7 0.0
## 22: 1960 0 0 0.0 3.7 6.9 3.5 9.5 2.7 5.5 0.0
## 23: 1961 0 0 0.0 0.0 2.4 1.7 4.6 8.7 15.1 7.7
## 24: 1962 0 0 0.1 0.0 2.5 18.1 5.9 26.5 21.8 6.4
## 25: 1963 0 0 0.0 0.0 5.6 3.2 5.0 5.4 9.8 5.5
## 26: 1964 0 0 0.0 0.0 0.0 7.6 5.0 1.0 9.7 5.6
## 27: 1965 0 0 0.0 0.0 4.3 8.1 10.5 11.7 37.1 2.0
## 28: 1966 0 0 0.0 0.0 1.6 1.2 11.9 6.8 14.2 0.4
## 29: 1967 0 0 0.0 0.2 3.4 12.7 35.3 23.7 2.6 0.2
## 30: 1968 0 0 0.0 0.3 0.8 2.4 10.6 2.2 0.8 0.4
## 31: 1969 0 0 0.0 0.0 4.9 28.7 21.6 5.3 7.3 0.3
## 32: 1970 0 0 0.0 2.4 3.8 33.2 9.8 4.3 8.6 1.3
## 33: 1971 0 0 0.0 0.0 6.3 5.5 19.9 13.9 7.0 1.9
## 34: 1972 0 0 0.0 0.0 13.4 12.8 12.2 7.6 10.4 8.0
## 35: 1973 0 0 0.0 0.0 1.1 15.3 11.6 11.3 0.4 2.0
## 36: 1974 0 0 0.0 0.0 0.1 17.9 2.5 15.7 7.7 7.3
## 37: 1975 0 0 0.0 0.0 1.2 6.1 27.4 9.0 18.3 2.2
## 38: 1976 0 0 0.0 0.0 16.2 5.6 12.8 5.1 13.6 0.0
## 39: 1977 0 0 0.0 2.3 1.4 8.3 13.4 1.8 14.6 1.8
## 40: 1978 0 0 0.0 3.0 11.7 14.2 6.8 4.6 8.5 1.9
## 41: 1979 0 0 0.0 0.0 16.5 15.1 14.2 13.5 8.4 0.7
## 42: 1980 0 0 0.0 0.0 7.7 1.7 12.9 8.8 13.7 8.5
## 43: 1981 0 0 0.0 0.0 0.9 2.8 4.6 11.0 0.1 1.7
## 44: 1982 0 0 0.0 0.9 14.0 10.6 46.4 7.4 10.9 4.8
## 45: 1983 0 0 0.0 1.4 3.6 19.3 3.2 10.8 14.3 21.8
## 46: 1984 0 0 0.0 0.0 30.4 21.0 10.8 9.3 17.3 9.8
## 47: 1985 0 0 0.0 0.3 2.0 16.3 13.1 4.2 36.8 0.0
## 48: 1986 0 0 0.4 0.0 23.9 13.5 10.3 12.3 8.7 0.4
## 49: 1987 0 0 0.0 0.0 4.4 4.2 5.5 1.2 2.1 0.0
## 50: 1988 0 0 0.0 0.3 4.5 7.5 19.5 4.5 3.7 2.4
## 51: 1989 0 0 0.0 0.2 15.8 7.2 6.0 17.3 22.7 0.8
## 52: 1990 0 0 0.0 0.0 11.3 7.0 1.1 10.7 3.2 2.2
## 53: 1991 0 0 0.0 0.0 5.0 11.7 6.5 14.2 4.4 1.5
## 54: 1992 0 0 0.0 8.2 46.9 6.7 5.0 5.9 10.8 0.6
## 55: 1993 0 0 0.0 1.3 12.2 9.2 12.0 5.3 6.9 0.5
## 56: 1994 0 0 0.0 0.0 7.7 4.5 24.3 12.0 1.7 5.5
## 57: 1995 0 0 0.0 0.0 6.2 6.5 4.2 2.1 10.4 0.2
## 58: 1996 0 0 0.0 0.7 6.6 16.1 14.5 1.2 14.1 2.3
## 59: 1997 0 0 0.0 0.0 16.8 23.7 14.2 4.0 14.3 0.6
## 60: 1998 0 0 0.0 0.0 8.6 3.3 20.4 1.1 11.6 0.0
## 61: 1999 0 0 0.0 0.0 0.1 3.1 33.1 4.2 16.0 0.0
## 62: 2000 0 0 0.0 0.0 0.7 7.3 18.2 7.7 1.0 1.3
## 63: 2001 0 0 0.0 0.0 9.8 30.2 9.4 16.5 8.6 1.3
## 64: 2002 0 0 0.0 0.1 9.4 8.0 9.5 3.1 15.7 20.2
## 65: 2003 0 0 0.0 0.6 1.4 3.0 5.1 10.7 13.2 1.0
## 66: 2004 0 0 0.0 0.0 9.4 16.1 10.7 19.7 10.4 0.0
## 67: 2005 0 0 0.0 0.0 0.5 1.8 8.6 8.0 6.6 0.0
## 68: 2006 0 0 0.0 0.0 5.1 14.5 2.3 2.1 20.4 0.0
## 69: 2007 0 0 0.0 0.0 0.2 4.3 5.5 12.6 11.0 1.9
## 70: 2008 0 0 0.0 0.0 0.4 18.1 2.0 4.8 18.0 1.6
## 71: 2009 0 0 0.0 0.0 4.3 17.4 8.4 10.9 1.5 2.5
## 72: 2010 0 0 0.0 2.8 0.0 20.9 3.1 13.9 0.0 0.0
## 73: 2011 0 0 0.0 0.0 9.8 33.6 17.0 16.1 8.2 1.9
## 74: 2012 0 0 0.0 0.0 3.0 7.3 4.6 6.1 1.3 0.0
## 75: 2013 0 0 0.0 0.0 0.8 15.0 4.6 15.1 13.8 17.9
## 76: 2014 0 0 0.0 0.0 1.1 15.9 22.7 18.4 4.7 7.0
## 77: 2015 0 0 0.0 0.0 9.4 5.6 5.4 4.9 6.8 0.3
## 78: 2016 0 0 0.0 0.0 5.1 9.5 4.1 12.1 5.4 0.5
## 79: 2017 0 0 0.0 0.0 2.3 15.8 8.4 0.3 4.7 0.5
## 80: 2018 0 0 0.0 0.1 0.6 6.4 20.4 15.9 8.8 26.1
## 81: 2019 0 0 0.0 0.3 4.0 6.7 6.8 39.0 10.5 9.8
## 82: 2020 0 0 0.0 0.0 14.3 11.3 9.8 7.5 1.3 7.3
## 83: 2021 0 0 0.0 9.3 8.8 12.4 7.8 5.9 4.0 0.5
## 84: 2022 0 0 0.0 0.0 1.2 21.5 10.5 10.3 5.1 1.6
## 85: 2023 0 0 0.0 0.4 13.0 19.8 22.3 15.5 15.5 3.8
## 86: 2024 0 0 0.0 2.7 0.5 2.1 2.0 7.0 15.2 0.0
## Winter_end_year JUL AUG SEP OCT NOV DEC JAN FEB MAR APR
## MAY JUN ANN
## <num> <int> <num>
## 1: 0.0 0 39.8
## 2: 0.0 0 45.1
## 3: 0.0 0 52.5
## 4: 0.0 0 23.9
## 5: 0.0 0 34.4
## 6: 0.0 0 26.9
## 7: 0.0 0 33.9
## 8: 3.0 0 39.9
## 9: 0.2 0 25.0
## 10: 0.0 0 49.1
## 11: 0.0 0 38.3
## 12: 0.0 0 51.6
## 13: 0.0 0 88.9
## 14: 0.0 0 79.0
## 15: 0.0 0 42.9
## 16: 2.4 0 25.7
## 17: 0.0 0 33.9
## 18: 0.0 0 45.2
## 19: 0.0 0 39.1
## 20: 0.0 0 21.2
## 21: 0.0 0 19.1
## 22: 0.0 0 31.8
## 23: 0.0 0 40.2
## 24: 0.0 0 81.3
## 25: 0.0 0 34.5
## 26: 0.0 0 28.9
## 27: 0.0 0 73.7
## 28: 0.0 0 36.1
## 29: 0.3 0 78.4
## 30: 0.0 0 17.5
## 31: 0.0 0 68.1
## 32: 0.0 0 63.4
## 33: 0.2 0 54.7
## 34: 0.0 0 64.4
## 35: 0.0 0 41.7
## 36: 0.0 0 51.2
## 37: 0.0 0 64.2
## 38: 1.2 0 54.5
## 39: 0.0 0 43.6
## 40: 0.0 0 50.7
## 41: 0.0 0 68.4
## 42: 0.0 0 53.3
## 43: 0.0 0 21.1
## 44: 0.0 0 95.0
## 45: 0.0 0 74.4
## 46: 0.0 0 98.6
## 47: 0.0 0 72.7
## 48: 0.0 0 69.5
## 49: 0.0 0 17.4
## 50: 0.0 0 42.4
## 51: 0.1 0 70.1
## 52: 0.0 0 35.5
## 53: 0.3 0 43.6
## 54: 0.0 0 84.1
## 55: 0.0 0 47.4
## 56: 0.0 0 55.7
## 57: 0.0 0 29.6
## 58: 0.0 0 55.5
## 59: 0.0 0 73.6
## 60: 0.0 0 45.0
## 61: 0.0 0 56.5
## 62: 0.0 0 36.2
## 63: 0.0 0 75.8
## 64: 0.0 0 66.0
## 65: 0.0 0 35.0
## 66: 0.0 0 66.3
## 67: 0.0 0 25.5
## 68: 0.0 0 44.4
## 69: 0.0 0 35.5
## 70: 0.0 0 44.9
## 71: 0.0 0 45.0
## 72: 0.0 0 40.7
## 73: 0.0 0 86.6
## 74: 0.0 0 22.3
## 75: 0.5 0 67.7
## 76: 0.0 0 69.8
## 77: 0.0 0 32.4
## 78: 0.0 0 36.7
## 79: 0.0 0 32.0
## 80: 0.0 0 78.3
## 81: 0.0 0 77.1
## 82: 0.0 0 51.5
## 83: 0.0 0 48.7
## 84: 0.0 0 50.2
## 85: 0.0 0 90.3
## 86: 0.0 0 29.5
## MAY JUN ANN#add snow to plant abund data:
a[ , date := as.IDate(SURVEY_START, format = "%m/%d/%Y") , ]
a[ , year := year(date) , ]
a[snow, on = .(year = Winter_end_year ) , annual_snowfall := ANN]
a[ ,.N , DOW][N>2, DOW]## [1] 62005500 62022500 27071100 81000300 80003400 2000400 62000600 40000200
## [9] 70002200 34003200 27006202 27009501 27011700 27104200 27104501 41004300
## [17] 27002800 27004800 27004500 70006900 70009100 27004400 27019200 2000900
## [25] 10000200 27007000 70005000 82009999 82011800 27010400 71014500 71014700
## [33] 62001100 10004401 10004800 27018600 82010100 82010300 10001300 10004402
## [41] 27005500 18024300 49013300 77004600 62000100 73015100 10004100 10008800
## [49] 29025000 13002700 62007500 27007100 27011800 3010700 10004200 19002200
## [57] 27007800 10004500 62005400 71001300 27019101 62023100 27019102 83004300
## [65] 47002600 47003200 73003700 10005300 19002500 82010400 27003501 82016300
## [73] 27013300 10004300 62004700 30013500 27062700 61000600 27003502 62005600
## [81] 10000700 66001800 62004800 82010600 82010900 10005100 86013900 82007400
## [89] 82001000 82010700 82000400a[ , , ] ## Key: <SURVEY_START, DOW>
## SURVEY_START DOW survey_ident totnsamp clpN lat_median lon_median
## <char> <int> <int> <int> <int> <num> <num>
## 1: 1/1/2010 62005500 1 53 25 NA NA
## 2: 1/1/2011 2009100 2 147 3 NA NA
## 3: 1/1/2013 62007100 3 50 3 NA NA
## 4: 2/22/2022 62022500 4 12 2 NA NA
## 5: 3/16/2021 27071100 5 125 16 44.97005 -93.38890
## ---
## 956: 6/9/2017 62004700 956 45 20 NA NA
## 957: 6/9/2022 10004402 957 108 5 44.86521 -93.68036
## 958: 6/9/2022 27007800 958 175 30 NA NA
## 959: 6/9/2022 27010400 959 185 75 NA NA
## 960: 6/9/2022 62005400 960 55 2 NA NA
## clpfoc date year annual_snowfall
## <num> <IDat> <int> <num>
## 1: 0.47169811 2010-01-01 2010 40.7
## 2: 0.02040816 2011-01-01 2011 86.6
## 3: 0.06000000 2013-01-01 2013 67.7
## 4: 0.16666667 2022-02-22 2022 50.2
## 5: 0.12800000 2021-03-16 2021 48.7
## ---
## 956: 0.44444444 2017-06-09 2017 32.0
## 957: 0.04629630 2022-06-09 2022 50.2
## 958: 0.17142857 2022-06-09 2022 50.2
## 959: 0.40540541 2022-06-09 2022 50.2
## 960: 0.03636364 2022-06-09 2022 50.2ggplot(a[DOW %in% a[ ,.N , DOW][N>2, DOW], , ], aes( annual_snowfall, clpfoc), )+
geom_point()+
geom_smooth(method = "lm")+
facet_wrap(~DOW, scales = "free")## `geom_smooth()` using formula = 'y ~ x'
a <- ggplot(a[DOW %in% a[ ,.N , DOW][N>2, DOW], , ], aes( annual_snowfall, clpfoc, group = as.factor(DOW)), )+
geom_point( aes(color = DOW) )+
geom_smooth(method = "lm", se = F, aes(color = DOW) )
ggplotly(a)## `geom_smooth()` using formula = 'y ~ x'So, from that plot I’d say the answer is that